针对高对比度场景下合成孔径雷达(SAR)图像的实时目标检测问题,提出一种基于级联恒虚警率(CFAR)的SAR图像目标快速检测算法,将二维图像的检测沿距离向和方位向拆分成两个一维的CFAR检测, 采用距离向-方位向级联检测器并加以分割关联方法对目标进行检测。首先,按距离向叠加后进行距离向检测,并进行分割关联以划分不同目标的区域;然后,对过检单元进行方位向检测得到目标位置;同时,进行分割关联,从而实现目标检测。文中利用仿真的SAR图像、MSTAR数据和实测数据进行实验。仿真结果表明:该算法具有速度快、检测率高的优点,满足实时处理要求。

A fast synthetic aperture radar (SAR) target detection method is proposed to solve the problem of real-time target detection of SAR image under high contrast condition. The two-dimensional (2D) detection process is divided into two one-dimensional (1D) constant false alarm rate (CFAR) detector operated along range and azimuth direction, respectively. The range detector is operated on the summation of all range profiles and indicates the locations of the targets along the range direction together with segmentation relevance. And the segmentation relevance can divide different targets. The azimuth detector locates the targets in the resulting range bins. Finally, the detected cells are fused to generate the region of the target using segmentation relevance. The experimental results of simulated image, MSTAR data and the measured data show that the algorithm has the advantage of fast speed and high detection rate and achieves the real-time processing requirements.

TN957.52

国家自然科学基金项目;长江学者奖励计划;高等学校学科创新引智基地111资助项目